Loading...
Loading...
Found 75 Skills
This skill should be used when users need to scrape content from websites, extract text from web pages, crawl and follow links, or download documentation from online sources. It features concurrent URL processing, automatic deduplication, content filtering, domain restrictions, and proper directory hierarchy based on URL structure. Use for documentation gathering, content extraction, web archival, or research data collection.
Batch download audio resources from websites, supports sites requiring login, with automatic deduplication and report generation
Enrich contacts and companies with verified emails, phones, and firmographic data. Also covers CRM data hygiene, deduplication, and bulk enrichment. Use when enriching leads, finding email addresses, cleaning CRM data, doing bulk enrichment, optimizing enrichment credits, setting up auto-enrichment, or fixing stale contact data. Do NOT use for building new prospect lists from scratch (use /sales-prospect-list), interpreting buying signals (use /sales-intent), or general Apollo platform help (use /sales-apollo).
Implementation workflows for Frappe scheduled tasks and background jobs (v14/v15/v16). Covers hooks.py scheduler_events, frappe.enqueue, queue selection, job deduplication, and error handling. Triggers: how to schedule task, background job, cron job, async processing, queue selection, job deduplication, scheduler implementation.
Modern React data fetching patterns. Use when implementing caching, deduplication, optimistic updates, or parallel loading with TanStack Query, SWR, or Suspense.
Generate and curate evaluation datasets — structured generation via dimensions-tuples-NL, quick from description, expansion from existing data, plus dataset maintenance through deduplication, rebalancing, and gap-filling. Use when creating eval data, expanding test coverage, or cleaning datasets. Do NOT use when sufficient real production data exists (use analyze-trace-failures instead). Do NOT use for evaluator creation (use build-evaluator).
Automates ingestion of documents into the Obsidian wiki (obsidian-wiki) using the wiki-ingest pipeline. Handles deduplication via manifest, frontmatter, and cross-links; triggers on user request within the obsidian-wiki project context.
Use when the user asks for a literature review, academic deep dive, research report, state-of-the-art survey, topic scoping, comparative analysis of methods/papers, grant background, or any request that needs multi-source scholarly evidence with citations. Also trigger proactively when a user question clearly requires academic grounding (e.g. "what's known about X", "compare approach A vs B in the literature", "summarize the field of Y"). Runs an 8-phase (Phase 0..7), script-driven research workflow across 7 federated sources (OpenAlex, arXiv, Crossref, PubMed, DBLP, bioRxiv, Exa) with optional Semantic Scholar / Brave MCP enrichment, with deduplication, transparent ranking, dual-backend citation chasing (OpenAlex + Semantic Scholar), self-critique, and structured report output with verifiable citations.
This skill should be used when the user asks to generate content such as titles, slogans, dialogues, or scripts. It provides content generation capabilities for various platforms (WeChat, Xiaohongshu, Zhihu, Douyin) with support for batch generation, history deduplication, and diversity guarantee. Supports podcast script generation with platform-specific adaptation.
GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.
This skill provides guidance for merging data from multiple heterogeneous sources (JSON, CSV, Parquet, XML, etc.) into a unified dataset. Use this skill when tasks involve combining records from different file formats, applying field mappings, resolving conflicts based on priority rules, or generating merged outputs with conflict reports. Applicable to ETL pipelines, data consolidation, and record deduplication scenarios.
Scheduler and background jobs syntax for Frappe/ERPNext v14/v15/v16. Use for scheduler_events in hooks.py, frappe.enqueue() for async jobs, queue configuration, job deduplication, error handling, and monitoring. Triggers on questions about scheduled tasks, background processing, cron jobs, RQ workers, job queues, async tasks.